Principal Scientist at Amazon | Ph.D. in Computer Science
Working on frontier-scale LLM pretraining. Leading pretraining effort for Rufus foundation models, spanning architecture (dense and sparse MoE), scaling laws, large-scale training recipes, and data mixture/curriculum design. Prior to joining Amazon, I received my Ph.D. in Computer Science at Carnegie Mellon University, advised by Prof. Kathleen M. Carley. My doctoral work focused on social network analysis and data mining.